Top Tech Jobs & Startup Jobs in Boston, MA

Software engineering interns contribute to production features, APIs, services, machine learning applications, data ingestion pipelines, and platform infrastructure. They participate in code reviews, deployment, observability, infrastructure as code, and engineering best practices while collaborating with experienced teams. Interns also receive opportunities for technical learning and cross-team exploration. The role requires algorithmic knowledge, software development experience through projects or open source, adaptability, and strong coding, documentation, and communication skills.

Develop and deploy machine learning solutions for generative AI platforms, LLM-powered applications, and AI toolkits. Interns will solve agentic design and LLM orchestration challenges, prototype and evaluate models, develop pipeline components, and support deployment across the ML lifecycle. The role involves collaboration with ML engineers, product managers, designers, and full-stack engineers, with mentorship and opportunities to work on scalable, production-ready systems.

Provide legal counsel on DeFi, digital assets, tokenization, and blockchain initiatives; draft, negotiate, and advise on complex commercial agreements and data licensing; evaluate protocols, oracle networks, and tokenized market models; support regulatory compliance, RFP responses, customer due diligence, and cross-functional product and commercial teams.

Sell enterprise loan management and administration software and services focused on loans, CLOs, and private credit. Generate new business, build and maintain client relationships, conduct market research, present demos with pre-sales, negotiate and close deals, collaborate with product, attend industry events, and meet or exceed sales targets.

Lead Kensho's AI partnerships and strategic client portfolio, driving partnership development, cross-functional deal execution, post-sale adoption, and commercial expansion of Kensho's APIs and AI products worldwide.

The MLOps Engineer focuses on developing tools and processes for ML workflows, empowering engineers, and ensuring high-quality model deployment. Key responsibilities include managing distributed systems, improving observability, and advocating best practices across teams.

As a Senior Full-Stack Software Engineer, you will develop AI-centric web applications, participate in architectural decisions, and mentor team members while managing project priorities and deliverables.

As a Senior Backend Engineer, you will develop secure and performant APIs, collaborate across teams, and drive technical development through mentorship and reviews.

Design, build, and scale retrieval-augmented generation (RAG) systems: chunking, embeddings, vector search, LLM orchestration, and production ML pipelines. Work cross-functionally to deploy robust retrieval, indexing, and evaluation solutions over large proprietary datasets, collaborating with MLOps, Product, and Design to productionize and maintain systems.

Build and productionize agentic AI systems that retrieve and synthesize structured and unstructured financial data. Work across the ML lifecycle: experiment, deploy, monitor, and evaluate agents and retrieval methods. Collaborate with data, product, design, and MLOps teams to create scalable, robust solutions that connect data to business insights.